To assess the creative outcomes in the networks, we use natural language processing tools for computationally capturing the semantic qualities of ideas. Divergent thinking/creativity leads individuals to generate numerous and varied responses to a given prompt [1]}. Two crucial dimensions of creativity, flexibility and originality, explicitly take into consideration the semantic qualities of ideas: flexibility is the
number of distinct semantic categories that a person accesses in his/her ideas, while originality is the extent to which a solution is semantically novel [2]}. If the network processes systematically make the stimulated ideas of the participants semantically similar, it hurts the divergence purposes. We estimate the semantic nature of the egos' idea-sets using neural word embeddings [3]}. To compute the semantic similarities between idea-sets, we employ the cosine similarity metric [4]}.
